The Relative Efficiency of Automatic and Discretionary Industrial Aid

For the last two decades, the primary instruments for UK regional policy have been discretionary subsidies. Such aid is targeted at “additional” projects - projects that would not have been implemented without the subsidy - and the subsidy should be the minimum necessary for the project to proceed. Discretionary subsidies are thought to be more efficient than automatic subsidies, where many of the aided projects are non-additional and all projects receive the same subsidy rate. The present paper builds on Swales (1995) and Wren (2007a) to compare three subsidy schemes: an automatic scheme and two types of discretionary scheme, one with accurate appraisal and the other with appraisal error. These schemes are assessed on their expected welfare impacts. The particular focus is the reduction in welfare gain imposed by the interaction of appraisal error and the requirements for accountability. This is substantial and difficult to detect with conventional evaluation techniques.

Incorporating jurisdiction issues into regional carbon accounts under production and consumption accounting principles

Despite increased public interest, policymakers have been slow to enact targets based on limiting emissions under full consumption accounting measures (such as carbon footprints). This paper argues that this may be due to the fact that policymakers in one jurisdiction do not have control over production technologies used in other jurisdictions. The paper uses a regional input-output framework and data derived on carbon dioxide emissions by industry (and households) to examine regional accountability for emissions generation. In doing so, we consider two accounting methods that permit greater accountability of regional private and public (household and government) final consumption as the main driver of regional emissions generation, while retaining focus on the local production technology and consumption decisions that fall under the jurisdiction of regional policymakers. We propose that these methods permit an attribution of emissions generation that is likely to be of more use to regional policymakers than a full global footprint analysis.

What is the Causal Effect of Information and Learning about a Public Good on Willingness to Pay?

In this study we elicit agents’ prior information set regarding a public good, exogenously give information treatments to survey respondents and subsequently elicit willingness to pay for the good and posterior information sets. The design of this field experiment allows us to perform theoretically motivated hypothesis testing between different updating rules: non-informative updating, Bayesian updating, and incomplete updating. We find causal evidence that agents imperfectly update their information sets. We also field causal evidence that the amount of additional information provided to subjects relative to their pre-existing information levels can affect stated WTP in ways consistent overload from too much learning. This result raises important (though familiar) issues for the use of stated preference methods in policy analysis.